The VLDB Journal

, Volume 19, Issue 3, pp 307–332 | Cite as

Analysis and evaluation of V*-kNN: an efficient algorithm for moving kNN queries

  • Sarana Nutanong
  • Rui Zhang
  • Egemen TaninEmail author
  • Lars Kulik
Regular Paper


The moving k nearest neighbor (MkNN) query continuously finds the k nearest neighbors of a moving query point. MkNN queries can be efficiently processed through the use of safe regions. In general, a safe region is a region within which the query point can move without changing the query answer. This paper presents an incremental safe-region-based technique for answering MkNN queries, called the V*-Diagram, as well as analysis and evaluation of its associated algorithm, V*-kNN. Traditional safe-region approaches compute a safe region based on the data objects but independent of the query location. Our approach exploits the knowledge of the query location and the boundary of the search space in addition to the data objects. As a result, V*-kNN has much smaller I/O and computation costs than existing methods. We further provide cost models to estimate the number of data accesses for V*-kNN and a competitive technique, RIS-kNN. The V*-Diagram and V*-kNN are also applicable to the domain of spatial networks and we present algorithms to construct a spatial-network V*-Diagram. Our experimental results show that V*-kNN significantly outperforms the competitive technique. The results also verify the accuracy of the cost models.


Spatial databases Nearest neighbor search 


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Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Sarana Nutanong
    • 1
    • 2
  • Rui Zhang
    • 1
  • Egemen Tanin
    • 1
    • 2
    Email author
  • Lars Kulik
    • 1
    • 2
  1. 1.Department of Computer Science and Software EngineeringUniversity of MelbourneMelbourneAustralia
  2. 2.NICTA VictoriaMelbourneAustralia

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